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Book Reviews / Recension

Parallelization of Reconstructability Analysis Algorithms.

Bush Jones published a series of papers providing sequential algorithms that are key to reconstructability analysis. These algorithms include the determination of unbiased reconstructions and a greedy algorithm for a generalization of the reconstruction problem. The implementation of these sequential algorithms provide scientists and mathematicians with the means of utilizing reconstructability analysis in systems modeling. The algorithms, however, are so computationally intensive that the system is limited to a very small set of variables. Many papers have been written applying reconstructability analysis and maximum entropy methods to various disciplines. Reconstructability analysis has the potential of dramatically impacting the scientific community, but the sequential algorithms leave the utilization of reconstructability analysis infeasible. The author has parallelized the reconstructability analysis algorithms developed by Jones, thereby, bridging the gap between theoretical application and feasible implementation. Since the goal of parallelization of these reconstructability analysis algorithms is to make them feasible to as many researchers as possible, a specific architecture is not assumed. It is assumed that the architecture employed is a multiple data architecture. That is, the architectural design needed for the implementation of these algorithms must have memory local to each processing element (PE). The parallel algorithms developed and presented here do not address the problems of communications between processors of particular architectures. These algorithms assume a reconfigurable bus system which is a bus system whose configuration can be dynamically altered thus allowing broadcasting and long-distance communications to be completed in constant time. It is noted that processor arrays with such reconfigurable bus systems have been designed. Frequently, parallel algorithms do not address the situation in which the number of values on which to operate is larger than the number of processors. However, since the purpose of the parallelization of these reconstructability analysis algorithms is to make them feasible for large structure systems, the parallelization given does address the situation in which the number of values on which to operate is larger than the number of processors available. Therefore, implementation of the algorithms involves simply incorporating the communication protocols between processors for the particular architecture employed

Fault Detection, Isolation and Restoration Test Platform Based on Smart Grid Architecture Model Using Intenet-of-Things Approaches

© 2018 IEEE. To systematically shift existing distribution outage management paradigms to smart and more efficient schemes, we need to have an architectural overview of Smart Grids to reuse the assets as much as possible. Smart Grid Architecture Model offers a support to design such emerging use cases by representing interoperability aspects among component, function, communication, information, and business layers. To allow this kind of interoperability analysis for design and implementation of Fault Detection, Isolation and Restoration function in outage management systems, we develop an Internet-of-Things-based platform to perform real time co-simulations. Physical components of the grid are modeled in Opal-RT real time simulator, an automated Fault Detection, Isolation and Restoration algorithm is developed in MATLAB and an MQTT communication has been adopted. A 2-feeder MV network with a normally open switch for reconfiguration is modeled to realize the performance of the developed co-simulation platform

Real-Time Control of Power Exchange at Primary Substations: An OPF-Based Solution

Nowadays, integration of more renewable energy resources into distribution systems to inject more clean en- ergy introduces new challenges to power system planning and operation. The intermittent behaviour of variable renewbale resources such as wind and PV generation would make the energy balancing more difficult, as current forecasting tools and existing storage units are insufficient. Transmission system operators may withstand some level of power imbalance, but fluctuations and noise of profiles are undesired. This requires local management performed or encouraged by distribution system operators. They could try to involve aggregators to exploit flexibility of loads through demand response schemes. In this paper, we present an optimal power flow-based algorithm written in Python which reads flexibility of different loads offered by the aggregators from one side, and the power flow deviation with respect to the scheduled profile at transmission-distribution coupling point from the other side, to define where and how much load to adjust. To demonstrate the applicability of this core, we set-up a real- time simulation-based test bed and realised the performance of this approach in a real-like environment using real data of a network. © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

Can a microscopic stochastic model explain the emergence of pain cycles in patients?

A stochastic model is here introduced to investigate the molecular mechanisms which trigger the perception of pain. The action of analgesic drug compounds is discussed in a dynamical context, where the competition with inactive species is explicitly accounted for. Finite size effects inevitably perturb the mean-field dynamics: Oscillations in the amount of bound receptors spontaneously manifest, driven by the noise which is intrinsic to the system under scrutiny. These effects are investigated both numerically, via stochastic simulations and analytically, through a large-size expansion. The claim that our findings could provide a consistent interpretative framework to explain the emergence of cyclic behaviors in response to analgesic treatments, is substantiated.Comment: J. Stat. Mech. (Proceedings UPON2008

Physical activity programs for balance and fall prevention in elderly: A systematic review

BACKGROUND: Due to demographic changes the world's population is progressively ageing. The physiological decay of the elderly adult may lead to a reduction in the ability to balance and an increased risk of falls becoming an important issue among the elderly. In order to counteract the decay in the ability to balance, physical activity has been proven to be effective. The aim of this study is to systematically review the scientific literature in order to identify physical activity programs able to increase balance in the elderly. METHODS: This review is based on the data from Medline-NLM, Pubmed, ScienceDirect, and SPORTDiscuss and includes randomized control trials that have analyzed balance and physical activity in healthy elderly over 65 years of age during the last decade. A final number of 8 manuscripts were included in the qualitative synthesis, which comprised 200 elderly with a mean age of 75.1 ± 4.4 years. The sample size of the studies varied from 9 to 61 and the intervention periods from 8 to 32 weeks. RESULTS: Eight articles were considered eligible and included in the quantitative synthesis. The articles investigated the effects of resistance and aerobic exercise, balance training, T-bow© and wobble board training, aerobic step and stability ball training, adapted physical activity and Wii Fit training on balance outcomes. Balance measures of the studies showed improvements between 16% and 42% compared to baseline assessments. CONCLUSIONS: Balance is a multifactorial quality that can be effectively increased by different exercise training means. It is fundamental to promote physical activity in the aging adult, being that a negative effect on balance performance has been seen in the no-intervention control groups

Community orientations toward a protective agency

Thesis (M.S.)--Boston Universit

IoT-Enabled Real-Time Management of Smart Grids with Demand Response Aggregators

Integration of widely distributed small-scale Renewable Energy Sources like rooftop Photovoltaic panels and emerging loads like plug-in Electric Vehicles would cause more volatility in total net demand of distribution networks. Utility-owned storage units and control devices like tap changers and capacitors may not be sufficient to manage the system in real-time. Exploitation of available flexibility in demand side through aggregators is a new measure that distribution system operators are interested in. In this paper, we present a developed real-time management schema based on Internet of Things solutions which facilitate interactions between system operators and aggregators for ancillary services like power balance at primary substation or voltage regulation at secondary substations. Two algorithms for power balance and voltage regulation are developed based on modified Optimal Power Flow and voltage sensitivity matrix, respectively. To demonstrate the applicability of the schema, we set-up a real-time simulation- based test bed and realised the performance of this approach in a real-like environment using real data of a network with residential buildings